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Ph.D. in Statistics

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Hakkında yorumlar Ph.D. in Statistics - Kurumda - Çankaya - Ankara

  • Program tanımları
    DOCTOR OF PHILOSOPHY CURRICULUM IN STATISTICS  

            Compulsory Courses for the Ph.D. Degree

    STAT 601 Advanced Probability Theory I 
    STAT 602 Advanced Probability Theory II 
    STAT 603 Advanced Theory of Statistics I 
    STAT

    Other Ph.D. Courses

    STAT 605 Theory of Linear and Nonlinear Statistical Models 
    STAT 606 Theory of Experimental Designs 
    STAT 607 Nonparametric Theory of Statistics 
    STAT 608 Probability Models and Stochastic Processes 
    STAT 609 Statistical Decision Theory 
    STAT 610 Sequential Analysis 
    STAT 611 Multivariate Analysis 
    STAT 612 Advanced Topics in Time Series Analysis 
    STAT 613 Advanced Topics in Life Testing and Reliability 
    STAT 614 Interpretation of Data I 
    STAT 615 Interpretation of Data II 
    STAT 616 Applications of Statistics in Industry 
    STAT 617 Large Sample Theory of Statistics 
    STAT 618 Mathematical Models and Response Surface Methodology 
    STAT 619 Advanced Topics in Regression and Analysis of Variance 
    STAT 620 Bayesian Inference 
    STAT 621 Robust Statistics 
    STAT 622 Discrete Multivariate Analysis 
    STAT 623 Spatial Statistics 
    STAT 630 Advanced Topics in Statistical Inference  
    STAT 632 Inference for Stochastic Processes 
    STAT 634 Theory of Stationary Random Functions 
    STAT 642 Seminar in Statistics 
    STAT 699 Ph.D. Thesis in Statistics 
    STAT 800-899 Special Studies


    DESCRIPTION OF GRADUATE PROGRAM


    STAT 601 Advanced Probability Theory I (3-0)3
    Notions of measure theory. General concepts and tools of probability theory. Independence; convergence; laws of large number. Random walks. Prerequisite: Consent of instructor.

    STAT 602 Advanced Probability Theory II (3-0)3
    Concept of conditioning. From independence to dependence. Ergodic theorems. Martingales and decomposibility. Brownian motion and limit distributions. Prerequisite: Consent of instructor.

    STAT 603 Advanced Theory of Statistics I (3-0)3

    Advanced topics in linear and non-linear statistical estimation. Prerequisite: Consent of instructor.

    STAT 604 Advanced Theory of Statistics II (3-0)3
    Advanced topics in statistical hypothesis testing. Prerequisite: Consent of instructor.

    STAT 605 Theory of Linear and Nonlinear Statistical Models (3-0)3
    General linear and nonlinear models. Topics related to the statistical inference in model building. Prerequisite: Consent of instructor.

    STAT 606 Theory of Experimental Designs (3-0)3
    Balanced and partially balanced incomplete block designs. Mixture designs. Factorial designs. Response surfaces. Optimal allocation of observations. Prerequisite: Consent of instructor.

    STAT 607 Nonparametric Theory of Statistics (3-0)3
    Rank testing and estimation procedures. Locally most powerful rank tests. Criteria for unbiasedness. Exact and asymptotic distribution theory. Asymptotic efficiency. Rank correlation. Sequential procedures. Prerequisite: Consent of instructor.

    STAT 608 Probability Models and Stochastic Processes (3-0)3
    Discrete and continuous time Markov chains and Brownian motion. Gaussian processes, queues, epidemic models, branching processes, renewal processes. Prerequisite: Consent of instructor.

    STAT 609 Statistical Decision Theory (3-0)3
    Decision theoretic approach to statistical problems. Complete class theorems. Bayes and minimax procedures. Multiple, sequential, invariant statistical decision problems. Prerequisite: Consent of instructor.

    STAT 610 Sequential Analysis (3-0)3

    Sequential probability ratio test. Approximations for stopping boundaries. Power curve and expected stopping time. Wald's lemmas. Bayes character of SPRT. Composite hypothesis. Ranking and selection CCH: (1-0)1. Prerequisite. Consent of instructor.

    STAT 611 Multivariate Analysis (3-0)3
    Advanced topics in multivariate statistical analysis. CCH: (1-0)1 Prerequisite: Consent of instructor.

    STAT 612 Advanced Topics in Time Series Analysis (3-0)3
    Univariate and multivariate time series analysis. Estimation and hypothesis testing in the time and frequency domains. CCH: (1-0)1. Prerequisite: Consent of instructor.

    STAT 613 Advanced Topics in Life Testing and Reliability (3-0)3
    Advanced topics in life models, reliability and hazard functions. Decision making in life testing. Design of experiments in life testing. CCH:(1-0)1. Prerequisite: Consent of instructor.

    STAT 614 Interpretation of Data I (3-0)3
    Application of statistical theory and procedures to various types of data. Use of computers and numerical methods are emphasized. CCH: (1-0)1. Prerequisite: Consent of instructor

    STAT 615 Interpretation of Data II (3-0)3
    Continuation of Stat. 614 CCH: (1-0)1. Prerequisite: Consent of instructor.

    STAT 616 Applications of Statistics in Industry (3-0)3
    A strong background in control charts including adoptations, acceptance sampling for attributes and variables data. Acceptance plans. Statistics of combinations. CCH: (1-0)1. Prerequisite: Consent of instructor.

    STAT 617 Large Sample Theory of Statistics (3-0)3
    Large sample properties of tests and estimates. Problems of consistency and various forms of asymptotic efficiencies. Irregular estimation problems. Inference from stochastic processes. CCH: (1-0)1. Prerequisite: Consent of instructor.

    STAT 618 Mathematical Models and Response Surface Methodology (3-0)3
    Two level factorial and fractional factorial designs, blocking, polynomial models, first order and second order designs, several responses, determination and optimum conditions, design criteria involving variance and bias. CCH: (1-0)1. Prerequisite: Consent of instructor.

    STAT 619 Advanced Topics in Regression and Analysis of Variance (3-0)3
    Development of linear classification models, components of variance for balanced designs, polynomial models, harmonic regression, crossed models for combined qualitative and quantitative factors. Analysis of variance for fixed, random and mixed effects models. Randomization. Violation of assumptions. CCH: (1-0)1. Prerequisite: Consent of instructor.

    STAT 620 Bayesian Inference (3-0)3
    Sampling theory, subjective probability, likelihood principles. Bayes theorem, Bayesian analysis of normal theory, inference problems, assessment of model assumptions, robustness of inference, analysis of variance, some aspects of multivariate problems. Bayesian aspects of statistical modelling. CCH: (1-0) 1. Prerequisite: Consent of instructor.

    STAT 621 Robust Statistics (3-0)3
    Transforming data. More refined estimators. Comparing location estimators. M and L estimators. Robust scale estimators and confidence intervals. Relevance to hypothesis testing. CCH: (1-0)1. Prerequisite: Consent of instructor.

    STAT 622 Discrete Multivariate Analysis (3-0)3
    Structural models for counted data, maximum likelihood estimates for complete tables, formal goodness of fit; summary statistics and model selection, maximum likelihood estimates for incomplete tables, estimating the size of a closed population, models for measuring change, analysis of square tables; symmetry and marginal homogeneity, measures of association and agreement, Pseudo-Bayes estimates of cell probabilities, asymptotic methods. CCH: (1-0)1. Prerequisite: Consent of instructor.

    STAT 623 Spatial Statistics (3-0)3
    Purely spatial processes. Spatial autocorrelation. Distribution theory for spatial statistics. Analysis for point patterns. Parametric spatial models. Estimation and testing procedures. CCH: (1-0)1. Prerequisite: Consent of instructor.

    STAT 630 Advanced Topics in Statistical Inference (3-0)3
    Several advanced topics of statistical inference suited to the needs of researcher. Prerequisite: Consent of instructor.

    STAT 632 Inference for Stochastic Processes (3-0)3
    Special models. Large sample theory for discrete and continuous parameter stochastic pocesses. Optimal testing. Bayesian, nonparametric and sequential inference for stochastic processes. Martingales. Stochastic differential equations. Prerequisite: Consent of instructor.

    STAT 634 Theory of Stationary Random Functions (3-0)3
    Second moment models of random variables and vectors. Correlation theory of random processes in the time and frequency domains. Theory of random fields in the time and frequency domains. Crossings and extremes of random functions. Applications. Prerequisite: Consent of instructor.

    STAT 642 Seminar in Statistics (Non-credit)
    Seminar course for Ph.D. students in Statistics

    STAT 699 Ph.D. Thesis in Statistics (Non-credit)

    STAT 900-999 Special Topics (4-0)Non-credit

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